{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "from pyvis.network import Network\n",
    "from  pyltp import Segmentor, Postagger, Parser, SementicRoleLabeller"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parser_main(sentence):\n",
    "    LTP_DIR=\"./ltp_data_v3.4.0\"\n",
    "    segmentor=Segmentor(os.path.join(LTP_DIR,\"cws.model\"))\n",
    "    postagger=Postagger(os.path.join(LTP_DIR,\"pos.model\"))\n",
    "    parser=Parser(os.path.join(LTP_DIR,\"parser.model\"))\n",
    "    labeller  =  SementicRoleLabeller(os.path.join(LTP_DIR,\"pisrl_win.model\"))\n",
    "    words=list(segmentor.segment(sentence))\n",
    "    postags=list(postagger.postag(words))\n",
    "    arcs=parser.parse(words,postags)\n",
    "    roles=labeller.label(words,postags,arcs)\n",
    "    roles_dict={key:{sub_key: [sub_key, *value] for sub_key,value in sub_data}for key,sub_data in roles}\n",
    "    return words,postags,arcs,roles_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "分词结果: ['苏轼', '是', '宋朝', '的', '著名', '文学家', '，', '黄庭坚', '是', '苏轼', '的', '好', '朋友', '。', '苏轼', '擅长', '写', '词', '，', '而', '黄庭坚', '擅长', '写', '诗', '。', '黄庭坚', '游览', '黄州', '，', '并', '赞叹', '黄山', '之', '美', '。', '黄庭坚', '探望', '苏轼', '，', '并', '一起', '吟诗', '作', '对', '。']\n",
      "语义角色标注结果: {1: {'A0': ['A0', 0, 0], 'A1': ['A1', 2, 5]}, 8: {'A0': ['A0', 7, 7], 'A1': ['A1', 9, 12]}, 15: {'A0': ['A0', 14, 14]}, 16: {'A1': ['A1', 17, 17]}, 21: {'A0': ['A0', 20, 20], 'A1': ['A1', 23, 23]}, 22: {'A1': ['A1', 23, 23]}, 26: {'A0': ['A0', 25, 25], 'A1': ['A1', 27, 27]}, 30: {'DIS': ['DIS', 29, 29], 'A1': ['A1', 31, 33]}, 36: {'A0': ['A0', 35, 35], 'A1': ['A1', 37, 37]}, 41: {'A0': ['A0', 35, 35], 'DIS': ['DIS', 39, 39], 'ADV': ['ADV', 40, 40]}, 42: {'ADV': ['ADV', 40, 40]}}\n"
     ]
    }
   ],
   "source": [
    "text=\"苏轼是宋朝的著名文学家，黄庭坚是苏轼的好朋友。苏轼擅长写词，而黄庭坚擅长写诗。黄庭坚游览黄州，并赞叹黄山之美。黄庭坚探望苏轼，并一起吟诗作对。\"\n",
    "words,postags,arcs,roles_dict=parser_main(text)\n",
    "print(\"分词结果:\",words)\n",
    "print(\"语义角色标注结果:\",roles_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ruler(words,postags,roles_dict,role_index):\n",
    "    v=words[role_index]\n",
    "    role_info=roles_dict[role_index]\n",
    "    if 'A0'in role_info.keys()and 'A1'in role_info.keys():\n",
    "        s=''.join([words[word_index]for word_index in range(role_info['A0'][1], role_info['A0'][2]+1) if postags[word_index][0]not in['w','u','x']and words[word_index]])\n",
    "        o=''.join([words[word_index]for word_index in range(role_info['A1'][1], role_info['A1'][2]+1) if postags[word_index][0]not in['w','u','x']and words[word_index]])\n",
    "        if s and o:\n",
    "            return'1',[s,v,o]\n",
    "        return '4',[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def triples_main(text):\n",
    "    sentences = [sentence for sentence in re.split(r'[？?！!。；;：:\\n\\r]', text) if sentence]\n",
    "    svos = []\n",
    "    for sentence in sentences:\n",
    "        words, postags, arcs, roles_dict = parser_main(sentence)\n",
    "        for idx in range(len(postags)):\n",
    "            if idx in roles_dict:\n",
    "                result = ruler(words, postags, roles_dict, idx)\n",
    "                if result and len(result) == 2:  # 确保返回的是 (flag, triple)\n",
    "                    flag, triple = result\n",
    "                    if flag == '1' and triple:  # 确保 triple 有效\n",
    "                        svos.append(triple)\n",
    "    return svos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "文本的三元组:svos=[['苏轼', '是', '宋朝著名文学家'], ['黄庭坚', '是', '苏轼好朋友'], ['苏轼', '擅长', '写词'], ['黄庭坚', '擅长', '诗'], ['黄庭坚', '游览', '黄州'], ['黄庭坚', '赞叹', '黄山美'], ['黄庭坚', '探望', '苏轼']]\n"
     ]
    }
   ],
   "source": [
    "svos=triples_main(text)\n",
    "print(\"文本的三元组:svos={0}\".format(svos))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_node(net,subs1,subs2):\n",
    "    if len(subs1) !=0:\n",
    "        for i in range(len(subs1)):\n",
    "            net.add_node(i,label=subs1[i],color=\"blue\")\n",
    "    if len(subs2) !=0:\n",
    "        for i in range(len(subs2)):\n",
    "            net.add_node(1000+i,label=subs2[i],color=\"green\")\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_node_id_dic(net):\n",
    "    dic_node_id={}\n",
    "    for i in net.node_ids:\n",
    "        dic_node_id[str(net.node_map[i][\"label\"])]=i\n",
    "    return dic_node_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_network(net,kg_list,node_id_dic):\n",
    "    for m in range(len(kg_list)):\n",
    "        try:\n",
    "            net.add_edge(node_id_dic[kg_list[m][0]], node_id_dic[kg_list[m][2]], label=kg_list[m][1], color=\"red\", width=2)\n",
    "        except AttributeError as e:\n",
    "                print(e,m)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: When  cdn_resources is 'local' jupyter notebook has issues displaying graphics on chrome/safari. Use cdn_resources='in_line' or cdn_resources='remote' if you have issues viewing graphics in a notebook.\n",
      "my_network.html\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"600px\"\n",
       "            src=\"my_network.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1d1e7d58898>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net=Network(notebook=True,directed=True)\n",
    "subs1=list(set(sublist[0] for sublist in svos))\n",
    "subs2=list(set(sublist[2] for sublist in svos))\n",
    "create_node(net,subs1,subs2)\n",
    "dic_node_id=create_node_id_dic(net)\n",
    "create_network(net,svos,dic_node_id)\n",
    "net.show(\"my_network.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_similar_semantics(net, node_id_dic, target_node):\n",
    "    node_id_dic_inverse = {v: k for k, v in node_id_dic.items()}  \n",
    "    target_node_id = node_id_dic[target_node]\n",
    "    adjacent_nodes = list(net.neighbors(target_node_id))           \n",
    "    similar_semantics = [node_id_dic_inverse[node_id] for node_id in adjacent_nodes]\n",
    "    return similar_semantics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "与目标词'苏轼'语义相关的词: ['写词', '宋朝著名文学家']\n"
     ]
    }
   ],
   "source": [
    "node_id_dic_inverse={v:k for k,v in dic_node_id.items()}\n",
    "similar=find_similar_semantics(net,dic_node_id,'苏轼')\n",
    "print(\"与目标词'苏轼'语义相关的词:\",similar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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